DC offset correction in a mobile communication system

ABSTRACT

A method of simultaneously determining a DC offset and a channel impulse response from a received signal in a mobile communication system. The received signal comprising a set of training sequence bits that have been modulated prior to transmission. The modulated signals experience a certain phase shift and are rotated by a certain angle. The received signal may also comprise a DC offset component that needs to be removed. By manipulation of the received signal samples with the knowledge of the original training sequence and method of modulation used, it is possible to simultaneously estimate the communication channel&#39;s impulse response and the DC offset by finding the Least Squares solution to a linear equation, such that the energy of the noise term introduced into the communication channel may be kept to a minimum. An improved technique utilising a priori information is also described.

[0001] The present invention relates particularly to DC offsetcorrection in a mobile communication system.

[0002] In a mobile communication system, signals are transmitted frommobile stations to a base station. A digital signal is prepared fortransmission by the mobile station by subjecting it to a modulationtechnique and using the resulting signal to modulate a carrier wave at acertain frequency. In transmission of the signal from a mobile stationto the base station, it may be subject to a number of different effects,depending on the environment through which the signal passes. Thatenvironment can vary considerably, depending, amongst other things, onthe distance between the mobile station and the base station, and theinterference caused by buildings and other structures in the area. It isquite common for a signal received from a mobile station at the basestation to comprise a number of different multi-path effects and also tobe subject to noise. Processing techniques at the receiver in the basestation are known to resolve the effects of the environment throughwhich the signal passes (communication channel) and also to take intoaccount the effects of noise. The first step at the receiver is tosample the incoming signal to take a number of digital samples from theincoming analogue signal, normally sampled at the expected bit rate ofthe transmitted signal. This can give rise to a DC offset componentwhich, if not removed, could corrupt the received signal samples suchthat the subsequent processing would be affected. In particular, thedigital signal samples may be processed by an equaliser to compensatefor the effects of the channel, and the known equalisers do not assumethat a DC offset will be present. There are other sources that mayintroduce a DC offset and the magnitude of the DC offset may vary. It isan aim of the present invention to obtain a reliable estimate of theoffset magnitude that needs to be removed from the signal, withoutdegrading the performance too much in the case that in fact no DC offsethas been introduced.

[0003] In current base stations, a possible DC component is removed fromthe received signal by digital signal processing means. This isperformed by removing the mean signal level from the real and imaginarycomponent separately. Thus, the received signal y is considered tocomprise both a real component and an imaginary component which arehandled separately. A mean value (Ey) can be calculated over a wholeburst to improve reliability. However, the transmitted data itself cancause the average value to have a false mean value, even in the casewhere there is no actual DC offset. This clearly degrades theperformance of the subsequent digital signal processing.

[0004] According to one aspect of the present invention there isprovided a method of simultaneously determining a DC offset (a_(dc)) anda channel impulse response (h) for a signal received from a firststation by a second station via a communication channel in a mobilecommunication system, the signal comprising digital data and a set oftraining sequence bits modulated prior to transmission, the methodcomprising: generating a set of reference signal samples representingthe training sequence bits and a set of rotation elements depending onthe modulation applied to the digital data prior to transmission;receiving and sampling the signal to produce a plurality of receivedsignal samples from the training sequence portion of the signal, thereceived signal samples possibly including a DC offset; and manipulatingthe received signal samples with the sets of received signal samples androtation elements in such a way as to simultaneously estimate the DCoffset (a_(dc)) and the channel impulse response (h) by minimising asquared distance function.

[0005] According to another aspect of the invention there is provided amethod of correcting for a DC offset in a signal received from a firststation by a second station via a communication channel in a mobilecommunication system, the signal comprising digital data and a set oftraining sequence bits modulated prior to transmission, the methodcomprising: receiving and sampling the signal to produce a plurality ofreceived signal samples from the training sequence portion of thesignal, the received signal samples possibly including a DC offset;manipulating the received signal samples with a set of reference signalsamples representing the training sequence bits and a set of rotationelements depending on the modulation applied to the digital data priorto transmission to simultaneously estimate the DC offset (a_(dc)) andthe channel impulse response (h) by minimising a squared distancefunction; and correcting the set of received signal samples in thedigital data portion of the signal by removing the thus estimated DCoffset from the received signal samples.

[0006] Preferably the squared distance function is F=|y−X.h−e.a_(dc)|²,where y represents the received signal samples, X represents thetraining sequence samples and e represents the set of rotation elements

[0007] According to a further aspect of the invention there is provideda system for simultaneously determining a DC offset and a channelimpulse response in a signal received from a first station by a secondstation via a communication channel in a mobile communication system,the signal comprising digital data and a set of training sequence bitsmodulated prior to transmission, the method comprising: circuitry forreceiving and sampling the signal to produce a plurality of receivedsignal samples from the training sequence portion of the signal, thereceived signal samples possibly including a DC offset; a memory holdinga set of reference signal samples representing the training sequencebits and a set of rotation elements depending on the modulation appliedto the digital data prior to transmission; an extended channel impulseresponse calculation unit for manipulating the received signal sampleswith the reference signal samples and the set of rotation elements insuch a way as to simultaneously estimate the DC offset (a_(dc)) and thechannel impulse response (h) by minimising a squared distance function;and means for extracting the DC offset from the simultaneous estimateperformed by the extended channel impulse response calculation unit.

[0008] The squared distance function is preferably F=|y−X.h|e.a_(dc)|²,where y represents the received signal samples, X represents thetraining sequence samples and e represents the set of rotation elements.

[0009] A mathematically convenient way of manipulating the samples is toorganise the received signal samples and the rotation elements as anextended training sequence matrix with m+1 columns, where m columnscontain the reference signal samples and the m+1^(th) column containsthe rotation elements.

[0010] The precise manipulation of the received signal samples with theextended reference matrix is discussed in more detail in the following.The inventor has found that by using this extended matrix in amathematical manipulation, which minimises the noise function w, anestimate can be made simultaneously of the channel impulse response andthe DC offset, which can then be removed. For a matrix manipulation, anextended channel impulse vector is generated comprising m channelimpulse response elements and a further element a_(dc).

[0011] The invention is particularly but not exclusively applicable to aTDMA communication system, where each signal comprises a transmissionburst.

[0012] The system described herein also includes an equaliser which usesthe channel impulse elements extracted from the extended channel impulsevector to account for effects of the communication channel. It willreadily be appreciated that after equalisation the data is subject to anumber of subsequent processing steps in order to extract the originaldata in the burst. These are not described herein because they are knownto a person skilled in the art and do not form part of the presentinvention.

[0013] For a better understanding of the present invention and to showhow the same may be carried into effect, reference will now be made byway of example to the accompanying drawings in which:

[0014]FIG. 1 is a diagram of a model of the transmission system;

[0015]FIG. 2 is a further diagram of a model of the system;

[0016]FIG. 3 is a diagram that represents the standard structure of asignal burst in a mobile communication system;

[0017]FIGS. 4a and 4 b are diagrams that show the construction of theextended training sequence matrix and the extended impulse responsevector, respectively;

[0018]FIG. 5 is a block diagram of a receiver;

[0019]FIG. 6 is a flow diagram illustrating the method of the DC offsetvalue removal;

[0020]FIG. 7 is a blcok diagram of a further improved receiver; and

[0021]FIG. 8 illustrates the performance improvements achieved using thereceiver of FIG. 7.

[0022]FIG. 1 is a diagram illustrating a model of a typical digitaltransmission system. It is shown together with an actual implementationof a cellular radio frequency (RF) communication system which is mappedto the model. The radio communication system comprises a base state BTS2 and at least one mobile station MS 4 in communication with each othervia a communication channel over an air interface. In the followingdescription, the mobile station is considered to be the transmitter andthe base transceiver station is considered to be the receiver. Referencenumeral 6 denotes the transmission signal being conveyed by the mobilestation 4 to the base transceiver station 2. It will readily beappreciated however that the system and techniques described in thefollowing are equally applicable where the base transceiver station 2 isacting as the transmitter and a mobile station MS 4 is acting as thereceiver.

[0023] For the purposes of the following description, the transmitter isconsidered to comprise a modulator which applies the necessarymodulation to the signal so that it can be transmitted over thecommunication channel. The communication channel itself can be modelledas a channel impulse response h and a noise component w that may betypically introduced as a result of some external perturbation to thesystem. The receiver side is considered to comprise a demodulator whichcarries out the necessary demodulation functions so that the originallytransmitted information can be recovered from the received signal. Thus,according to the model of FIG. 1 the modulator is considered as carryingout a modulation process and the demodulator is considered as carryingout a demodulation process. The assumption is made herein that it isnecessary to apply a modulation to the signal prior to transmission, andthus to carry out an according demodulation process on receipt of thesignal. In FIG. 1, X is used to denote the signal prior to modulationand y is used to denote the recovered received signal afterdemodulation.

[0024] For the purpose of the present description, the modulation anddemodulation process can be thought of as introducing two components.These components are a DC offset (a_(dc)) and a phase shift vector (e)which may be modelled as shown in FIG. 2. That is, the received signal ydiffers from the channel-equalised version of the input signal x bya_(dc) and e. The magnitude of the DC offset (a_(dc)) is unknown andcauses problems with subsequent DSP techniques on the received signal ifit is not removed. The phase shift vector (e) depends on the modulationmethod used, and thus is known. EDGE (Enhanced Data Rates for GSMEvolution) modulation is an example. For EDGE the selected modulation is3 pi/8-8 PSK. In the basic 8 PSK constellation there are 8 equidistantpoints on the unit circle. This means that the transmitted symbols x_(k)can have eight possible values,

[0025] x_(k)=e^(j*i*pi/4), where i can have values from 0 to 7 dependingon the symbol value (j is complex indicator).

[0026] Now for 3 pi/8-8 PSK, the 3*pi/8 shift means that the transmittedsymbols are multiplied by a 3 pi/8 rotating value. So,

[0027] x_(k)′=x_(k)*e^(j*k*3*pi/8), where k is the symbol index.

[0028] This means that in the receiver the transmitted samples (x_(k)′)must be derotated by e^(−j*k*3*pi/8) to get the original 8PSKconstellation (x_(k)) to be equalised. This derotation will also makethe DC offset rotate by e^(−j*k*3*pi/8).

[0029]FIG. 3 illustrates a normal burst in a mobile communication systemaccording to the GSM standard. This figure represents a burst receivedat a base station. For a TDMA system according to the GSM standard,mobile stations transmit bursts as modulated signals on respectivecarrier frequencies according to channels allocated to respective callsby a base station controller. One frequency channel may support up toeight calls, each call being associated with a respective burst, whereeach call is allocated a time slot in a TDMA frame in which to send theburst. Further details of a TDMA system according to the GSM standardare not described herein because they are known to a person skilled inthe art. The normal burst contains two packets of 58 bits (DATA)surrounding a training sequence (TRS) of 26 bits. Three tail bits (TS)are added to each end of the normal burst. The training sequence (TRS)is a predetermined sequence of bits which are sent by the mobile station(MS) and is known at the base station controller (BSC). It is normallyutilised at the base station controller to estimate the impulse responseof the channel over which the burst is sent. According to the systemdescribed in the following, it is used to jointly calculate the impulseresponse and the DC offset. The actual information which is transmittedis located in the data bits (DATA) of the burst.

[0030] Thus, the technique described in the following is based on thejoint estimation of the channel impulse response and DC offset using thetraining sequence TRS. X is used in the following to denote the trainingsequence because as far as the model of FIG. 1 is concerned, that is theinput signal of interest for the following mathematical explanation.Before describing the system, an explanation of the mathematicaltechniques which are used in the system is set out.

[0031] The linear equation based on the models illustrated in FIGS. 1and 2 is formally stated in Equation 1.

y=X.h+e.a _(dc) +w   (Equation 1)

[0032] Each digital sample of the signal is modulated prior totransmission and therefore experiences a phase shift depending on themodulation technique used. This phase shift is also known as rotationand may be represented as: e^(−jθ). Therefore a vector (e) may be formedwhich comprises the phase shifts of all the samples of the trainingsequence that are used as in Equation 2.

e=[e ^(−j.k.θ) e ^(−j.(k−1).θ) . . . e ^(−j.(k−n+1).θ)]^(T)   (Equation2)

[0033] where:

[0034] θ—represents the phase shift (and depends on the method ofmodulation that is implemented).

[0035] k—represents the time indexes (indices) of the samples taken ofthe training sequence.

[0036] n—represents the number of samples used in the training sequence.

[0037] For example, if GMSK modulation is used, the samples are allrotated by 90 degrees (θ=π/2). Therefore, these samples will need to bederotated before the received signal is equalised.

[0038] Equation 4 can now be formulated by creating an extended trainingsequence matrix (X_(e)) and an extended impulse response vector (h_(e))incorporating the phase shift vector (e) and the DC offset (a_(dc))elements into the aforementioned matrix (X) and vector (h) as shown byEquation 3: $\begin{matrix}{X_{e} = {{\begin{bmatrix}X & e\end{bmatrix}\quad {and}\quad h_{e}} = \begin{bmatrix}h \\a_{d\quad c}\end{bmatrix}}} & ( {{Equation}\quad 3} )\end{matrix}$

 y=X _(e) h _(e) +w   (Equation 4)

[0039]FIG. 4a illustrates the original training sequence and extendedtraining sequence matrices. FIG. 4b illustrates the original impulseresponse and the extended impulse response vectors,

[0040] where:

[0041] m—represents the amount of impulse response taps (i.e. i=0 . . .4)

[0042] n—represents the length of samples used for impulse responseestimation (i.e. k=26).

[0043]FIG. 4a illustrates that the matrix size is determined by thenumber of columns and rows that constitute the matrix. It is importantto note that the original training sequence matrix (X) is composed ofknown elements. The number of columns m corresponds to the number ofdiscrete taps that the proposed model of the impulse response filterwill possess. The number of rows n is determined by the length ofsamples used from the training sequence for impulse response estimation.This makes the matrix size and the computational power required by theDSP flexible depending on the user's specification. The extendedtraining sequence matrix (X_(e)) is created by adding an additionalcolumn of elements to the known training sequence matrix (X). Thisadditional column contains the elements of the phase shift vector (e)(also known) and the size of the extended training sequence matrix isnow m+1 columns by n rows.

[0044]FIG. 4b shows the original and extended impulse response vectors(h/h_(e)). The extended impulse response vector has m+1 elements whichmeans it can readily be manipulated with the m+1 columns provided by theextended training sequence matrix (X_(e)). The last element in theimpulse response vector is the DC offset term (a_(dc)).

[0045] The extended impulse response vector he can be found by ensuringthat adequate estimates for the channel impulse response and DC offsetcan be made by minimising the function F=|y−X.h−e.a_(dc)|², where Frepresents the Least Squares solution to minimise the noise (w). Usingthe matrix format, Equation 5 results.

h _(e)=(X _(e) ^(H) .X _(e))⁻¹ .X _(e) ^(H) .y   (Equation 5)

[0046] where; y represents the received signal, and

[0047] X_(e) ^(H) represents the complex conjugate transpose of theextended matrix.

[0048] Thus, this has effectively solved for the required number ofchannel impulse response elements and also for the DC offset term(a_(dc)).

[0049] A block diagram for implementing the technique will now beillustrated in FIG. 5.

[0050] It should be understood that the various blocks in FIG. 5,although illustrated as separate interconnected entities, do notnecessarily represent separate physical entities, but are intended torepresent diagrammatically the various steps which are carried out. Theblocks could be implemented as circuits or a suitably programmedmicroprocessor may effect each of the functions which is individuallyassigned to the blocks. Moreover, a receiver for a BTS or MS will have anumber of components which are not illustrated in FIG. 5 and which havebeen omitted for the sake of clarity and because they do not pertain tothe present invention. An antenna 12 receives the transmitted signal 10via the air interface from the mobile stations. The antenna 12 isconnected to RF circuitry 14. The RF circuitry 14 operates on thereceived burst to downshift the frequency to the baseband frequency andto sample the burst to provide from the analogue input signal digitalsampled values. The output of RF circuitry 14 is denoted y and is asampled burst comprising a plurality of signal samples y_(i), sampled atthe expected bit rate of the transmitted signal. As described above,FIG. 3 illustrates the burst construction. The output of the RFcircuitry 14 is supplied along line 16 to a TRS extractor 18 and also toa subtraction circuit 40 the purpose of which will be described later.

[0051] The training sequence TRS is extracted from the received signal yand supplied along line 20 to an extended channel impulse response unit22. It will be appreciated that TRS is represented at this point as k(k=26 in this embodiment) digital signal samples.

[0052] The extended channel impulse response unit 22 is used tocalculate the so-called extended channel impulse response he whichincludes not only the “normal” channel impulse response tapsh(i)_(i=0 . . . 4). but also the required DC offset value a_(dc). Inknown receivers, the channel impulse response unit uses the receivedtraining sequence TRS and calculates an estimated channel impulseresponse h by calculating the cross correlation between the receivedtraining sequence TRS and the known training sequence which is stored atthe receiver, TRSref. In the present case, somewhat differentcalculations are performed according to the mathematical conceptsdescribed earlier. It will be appreciated that the extended CIR unit 22comprises a suitably programmed processor for implementing thecalculation. The extended channel impulse response unit 22 has access toa memory 34 in which there is prestored at least one so-called A matrix.The A matrix is calculated by manipulating the transpose of the complexconjugate of the extended training sequence matrix X_(e) ^(H) as definedin Equation 6. The formation of the extended training sequence matrixX_(e) has been described and is illustrated in FIG. 4a.

A=(X _(e) ^(H) .X _(e))⁻¹ .X _(e) ^(H)   (Equation 6)

[0053] It will be readily understood that the diagrammatic layout of thememory 34 is for illustration purposes only and the use of the storagecapacity can be in any appropriate manner. Moreover, a number ofdifferent A matrices can be precalculated and stored to take intoaccount different phase shift vectors (e) and different trainingsequences. The extended CIR unit 22 can select the appropriate A matrix.The memory 34 also holds the phase shift vector (e) for a purpose whichwill be described later.

[0054] Therefore, the extended channel impulse response unit 22 has twoinputs. One input is the training sequence TRS of the received signaland the other is the calculated A matrix. The extended CIR unit (22)calculates the extended channel impulse response vector h_(e) usingEquation 5 (noting the value of A in Equation 6). The matrixmanipulations (based on the Least Squares minimisation of the noisefunction F) allow the impulse response h and DC offset a_(dc) values tobe solved by performing only one matrix multiplication, i.e.(h_(e)=A.y).

[0055] A DC offset extract unit 26 extracts the DC offset a_(dc) fromh_(e) and supplies it to a multiplier circuit (30). The other input tothe multiplier circuit is the known phase shift vector e stored in aportion of memory. If the modulation method used resulted in no rotationof the samples, then this vector would comprise a set of ones. In eitherevent, the phase shift vector (e) is multiplied with the DC offset(a_(dc)). The product a_(dc).e is then subtracted from the receivedsignal y at the subtraction circuit (40). The output is a correctedsignal y_(c) that is fed to an equaliser (48). The equaliser (48) alsoreceives the normal channel impulse response h extracted from theextended channel impulse response vector h_(e) by an extract h circuit(42). The equaliser is known in the art and allows the data DATA y inthe burst to be recovered.

[0056] In brief, the equaliser, as the name suggests, is a filter usedto negate the effects of the communication channel (such as timedispersion, fading, etc.). The calculation of the impulse responsevector allows an equalising filter to be constructed modelled on theinverse of the impulse response taps calculated and reflected in theelements of the first m rows of the matrix shown in FIG. 4b.

[0057]FIG. 6 is a flow diagram which describes the processing sequenceas two parts. The first part (S1 to S3) can be done prior to receipt ofa signal as part of a set up procedure. The second part is accomplishedin the circuitry of FIG. 5. The first step S1 is to calculate the phaseshift vector (e), based on the known modulation technique. Next, at S2,the extended training sequence matrix (X_(e)) is created. It is assumedthat the training sequence matrix X is already known. The phase shiftvector is added as a final column of this matrix resulting in theextended matrix (X_(e)=[X e]).

[0058] The final processing operation S3 performed in the set up phaseis to calculate the new matrix A given by Equation 6. In operation, theextended CIR unit 5 receives two input signals. The first input S4 a isthe training sequence portion TRS of the received signal. The secondinput S4 b is the A matrix. The extended impulse response vector (h_(e))may be calculated at S5 from Equation 5, and contains an additionalelement over the normal h taps, i.e. the DC offset (a_(dc)). Next at S6,the DC offset element a_(dc) is extracted from the extended CIR vectorhe. Finally at step S7, Equation7 is used to obtain the corrected signalthat is sent to the equaliser circuit.

y _(c) =y−e.a _(dc)   (Equation 7)

[0059] This takes into account whether the samples have been derotatedor not. If there is no derotation the e vector is a vector of ones. Thecorrect signal is sent (step S8) to the equaliser after removal of thecorresponding DC offset components.

[0060] It should be noted that FIG. 1 and Equation 1 are defined as amodel of the transmission system and therefore it is assumed that anoise component (w) will be present. However, Equation 5 is known as theLS (Least Squares) solution to a linear equation (i.e. Equation 1). Thisimplies that the estimated parameters, h and a_(dc) are chosen so thatthe energy of the noise term (w) is kept to a minimum.

[0061] A further improvement in the inventive technique proposed aboveis now described with reference to FIG. 7. The inventive techniquedescribed hereinabove results in an increased cost in the estimation dueto an increase in noise caused by the number of parameters beingincreased. In the further improvement to the invention describedhereafter, it is proposed to minimize the cost of the estimation bytaking into account a priori information. Before describing the improvedsystem, an explanation of the mathematical techniques which are utilizedin the improved system is set out.

[0062] As described hereinabove, the offset can be selected according tothe modulation used. This is formulated, from equations 3 and 4, as:

Y=X _(e) h _(e) +w, where ${X_{e} = {{\begin{pmatrix}X & e\end{pmatrix}\quad {and}\quad h_{e}} = \begin{pmatrix}h \\a_{d\quad c}\end{pmatrix}}},$

[0063] The extended impulse response vector can be estimated using aknown LMMSE estimator, which can be written as:

h _(e) =E(h _(e))+(C _(hh) ⁻¹ +X _(e) ^(H) C _(w) ⁻¹ X _(e))⁻¹ X _(e)^(H) C _(w) ⁻¹(y−X _(e) E(h _(e))), where

[0064] C_(w) is noise covariance matrix and

[0065] C_(hh) is estimated parameter covariance matrix

[0066] The DC offset can simply be removed before sample derotation asy=y−a_(dc) and after derotation as y=y−ea_(dc)

[0067] This format cannot be used straight away as the noise covariancematrix and the impulse response and DC-offset covariance matrices areunknown. In order to be able to use the proposed LMMSE estimator it isnecessary to make certain a priori assumptions.

[0068] First it is assumed that E(h_(e))=0. As the received signal phaseis unknown, the expected value goes to zero. Also the expected DC-offsetis zero. It is assumed that the DC-offset can have a random phase andtherefore the expected value is zero.

[0069] The second assumption can be made for the noise covariancematrix. In this context the noise is assumed to be white, so the noiseco-variance matrix can be written as: ${C_{w} = \begin{pmatrix}\delta^{2} & 0 & \ldots & 0 \\0 & \delta^{2} & \ldots & 0 \\\ldots & \ldots & \ldots & \ldots \\0 & 0 & 0 & \delta^{2}\end{pmatrix}},$

[0070] where δ² is the noise variance of the starting point linearmodel.

[0071] The third assumption is that separate impulse response taps areuncorrelated. Therefore the parameter covariance matrix can be writtenas: $C_{hh} = \begin{pmatrix}{h_{0}^{*}h_{0}} & 0 & \ldots & \ldots & 0 \\0 & {h_{1}^{*}h_{1}} & 0 & \ldots & 0 \\\ldots & \ldots & \ldots & \ldots & ... \\\ldots & \ldots & \ldots & {h_{i}^{*}h_{i}} & \ldots \\0 & 0 & \ldots & \ldots & {d\quad c^{*}d\quad c}\end{pmatrix}$

[0072] Where h_(i) refers to impulse response tap i and dc refers toDC-offset.

[0073] Using these assumptions the LMMSE estimator can be simplified andit can be rewritten as:

h _(e)=(δ² C _(hh) ⁻¹ +X _(e) ^(H) X _(e))⁻¹ X _(e) ^(H) y, where$C_{hh}^{- 1} = \begin{pmatrix}{{1/h_{0}^{*}}h_{0}} & 0 & \ldots & \ldots & 0 \\0 & {{1/h_{1}^{*}}h_{1}} & 0 & \ldots & 0 \\\ldots & \ldots & \ldots & \ldots & ... \\\ldots & \ldots & \ldots & {{1/h_{i}^{*}}h_{i}} & \ldots \\0 & 0 & \ldots & \ldots & {{1/d}\quad c^{*}d\quad c}\end{pmatrix}$

[0074] It can be noted that if the variance δ²→0 the estimator comesback to classical LSE and if the autocorrelation properties of thetraining sequence are properly chosen the estimator comes back to basiccorrelation method.

[0075] In the proposed extended impulse response vector there are twounknown parameters C_(hh) and δ² still required for the DC-offsetestimation. There are several possibilities to gain this information.One simple approach is to optimise the equation for particular C/(I+N)value and use a fixed value for variance estimate. The C_(hh) could be afixed matrix according to known a priori information regarding theimpulse response.

[0076] In the present invention, the a priori information is used forshortening the LMMSE equation as described in the preceding paragraphs.

[0077] When the above-defined shortened LMMSE equation is used, theremay be a priori information about the channel or the dc offset. So, forexample, it may be known that the DC offset does not exist in certainchannels (for certain carrier frequencies). Such information may be usedin the DC offset estimator without needing to estimate the parametersfrom received data. Thus in such a scenario there is a prioriinformation available relating to the estimated parameters.

[0078] Such information about the DC offset could be measured fromprevious and/or current time-slots. The LMMSE equation may then utilizethis information. The utilisation of this information by the LMMSE isnot actually a usage of a priori information, because such informationis created by the estimator itself.

[0079] A further practical approach is based on two-phase channelestimation and is now described with reference to FIG. 7. As can be seenfrom FIG. 7, the extended CIR block 22 of FIG. 5 is replaced, in thepreferred embodiment of FIG. 7, by three blocks: an impulse responseestimation block 100, an estimate variance block 102 and an LMMSE block104. The memory is provided with the e values as in FIG. 5. The A valuesare not utilized, but in one embodiment are preferably replaced by thematrix C_(hh).

[0080] The impulse response estimation 100 operates to provide aninitial impulse response which in one embodiment is used to provide thevalues of the matrix C_(hh). The variance is estimated in block 102based on the output of the block 100. It should be noted that the use ofthe estimate variance block 102 is optional. In this embodiment theoutput of the impulse response estimation block 100 is used by theLMMSE, in accordance with the theory set out above, as a prioriinformation for estimating the impulse response in accordance with theimproved technique. In such an embodiment the values C_(hh) are notstored in the memory 34, as they are generated by the impulse responseestimation 100.

[0081] In a further embodiment, the impulse response estimation block100 is not provided, and the values of the matrix C_(hh) are stored inthe memory 34. The stored matrix C_(hh) provides the a prioriinformation to the LMMSE 104.

[0082] The output of the LMMSE is further processed in blocks 26 and 42in the identical manner to the outputs of the block 22 in FIG. 5.

[0083] It should be noted that the estimate variance block 102 does notform an essential part of this improvement to the invention. Theestimate variance block 102 may be similarly provided at the input tothe block 22 in FIG. 5. In FIG. 5, it is assumed that the functionalityof the estimate variance block is provided in the equalizer 48.

[0084] The important aspect of this improvement to the present inventionis that a priori information is used in determining the impulse responsewith the dc offset removed. This a priorii information may be providedin a number of ways. In the two example implementations described hereinthe a priori information is provided either by carrying out an initialimpulse response estimation, or by pre-storing appropriate values. Whereappropriate values are pre-stored, they may be generated based onsimulation.

[0085] Thus in the preferred embodiment described with reference to FIG.7, a preliminary DC-offset and impulse response are first estimatedusing a classical estimator (for example an LSE) in block 100. ThisDC-offset is subtracted from received samples and the impulse responseestimate is then used to estimate the signal variance in block 102. Thisvariance is then used in second phase in the improved impulse responseestimation method in block 104. An estimate of the C_(hh) is requiredfor the improved method, and this can be preferably achieved by forexample estimating the covariance matrix C_(hh) from the preliminaryimpulse response estimate.

[0086] As a sub-optimum method the following formula can be derived alsofor DC-offset correction. The weight coefficient is extended by theDC-offset estimator$a_{ei} = \frac{{h_{ei}}^{2}}{{h_{ei}}^{2} + {e_{i}^{*}e_{i}}}$

[0087] The e_(i)*e_(i) is dependant on the receiver signal variance by aconstant (it can be easily analysed) and the above can be written:${a_{ei} = \frac{{h_{ei}}^{2}}{{h_{ei}}^{2} + {p\quad \delta^{2}}}},{where}$p  is  user  selectable  constant  andδ²  is  received  signal  variance

[0088] The improved technique requires handling of matrices, whichincreases the complexity of the DC-offset estimation. However theDC-offset estimation will be obtained at the same time that the channelimpulse response is estimated, so the total complexity does not increasesignificantly. Most of the matrixes are diagonal and the amount ofrequired calculations can therefore be kept small.

[0089] Considering this improved technique for a GSM system requires 6×6matrix inversion. Therefore the improved technique is implementable.According to simulation results achieved the improved technique is ableto improve the receiver performance in all GSM 5.05 channel types aswell as in different C/(I+N) situations. The first simulations have beenperformed with receiver without diversity using the double correlationmethod. The achieved gain over that receiver is significant.

[0090]FIG. 8 shows one simulation. The reference for DC-offset estimatoris LSE based estimator and LMMSE based estimator is reference forperformance. LSE 1 is LSE estimator in the case that a DC-offset exists,and the estimated DC-offset is removed. LSE 2 is LSE estimator in thecase that no DC-offset exists, and the estimated DC-offset is removed.LMMSE 1 is a proposed improved method based LMMSE estimator in the casethat DC-offset exists and the estimated DC-offset is removed. LMMSE 2 isproposed improved method based LMMSE estimator in the case that noDC-offset exists and the estimated DC-offset is removed. LMMSE ref 1 isLMMSE estimator in the case that DC-offset exists and the DC-offset isnot estimated and not removed. LMMSE ref 2 is LMMSE estimator in thecase that no DC-offset exists and the DC-offset is not estimated and notremoved.

1. A method of simultaneously determining a DC offset (a_(dc)) and achannel impulse response (h) for a signal received from a first stationby a second station via a communication channel in a mobilecommunication system, the signal comprising digital data and a set oftraining sequence bits modulated prior to transmission, the methodcomprising: generating a set of reference signal samples representingthe training sequence bits and a set of rotation elements depending onthe modulation applied to the digital data prior to transmission;receiving and sampling the signal to produce a plurality of receivedsignal samples from the training sequence portion of the signal, thereceived signal samples possibly including a DC offset; and manipulatingthe received signal samples with the sets of received signal samples androtation elements in such a way as to simultaneously estimate the DCoffset (a_(dc)) and the channel impulse response (h) by minimising asquared distance function.
 2. The method of claim 1 wherein the squareddistance function is F=|y−X.h−e.a_(dc)|², where y represents thereceived signal samples, X represents the training sequence samples ande represents the set of rotation elements.
 3. A method of correcting fora DC offset in a signal received from a first station by a secondstation via a communication channel in a mobile communication system,the signal comprising digital data and a set of training sequence bitsmodulated prior to transmission, the method comprising: receiving andsampling the signal to produce a plurality of received signal samplesfrom the training sequence portion of the signal, the received signalsamples possibly including a DC offset; manipulating the received signalsamples with a set of reference signal samples representing the trainingsequence bits and a set of rotation elements depending on the modulationapplied to the digital data prior to transmission to simultaneouslyestimate the DC offset (a_(dc)) and the channel impulse response (h) byminimising a squared distance function; and correcting the set ofreceived signal samples in the digital data portion of the signal byremoving the thus estimated DC offset from the received signal samples.4. The method of claim 3 wherein the squared distance function isF=|y−X.h−e.a_(dc)|², where y represents the received signal samples, Xrepresents the training sequence samples and e represents the set ofrotation elements.
 5. A method according to claim 1, wherein the set ofreference signal samples representing the training sequence bits and theset of rotation elements depending on the modulation applied to thedigital data prior to transmission are arranged as an extended trainingsequence matrix; and wherein the manipulating step results in anextended channel impulse vector which comprises an estimate of the DCoffset (a_(dc)) and a plurality of the channel impulse response elements(h).
 6. A method according to claim 5, wherein the manipulation carriedout with the extended reference matrix and the received signal samplesto generate the extended channel impulse vector h_(e) is as follows: h_(e)=(X _(e) ^(H) .X _(e))X _(e) ^(H) .y where h_(e) represents theextended channel impulse vector, X_(e) represents the extended referencematrix, y represents the received signal samples and X_(e) ^(H)represents the complex conjugate transpose of the extended referencematrix.
 7. A method according to claim 5, comprising the additional stepof extracting the channel impulse elements from the extended channelimpulse vector and using the channel impulse elements in an equalisationstep to remove from the received signal samples the effects of thecommunication channel for the signal.
 8. A method according to claim 1wherein the signal comprises a transmission burst in a TDMA mobilecommunication system.
 9. A method according to 1, wherein the receivedsignal is sampled at the expected transmitted bit rate of the signal toproduce a number of received signal samples corresponding to the numberof bits of digital data and training sequence bits.
 10. A methodaccording to claim 1 in which the channel impulse response is estimatedusing a priori information.
 11. A method according to claims 10, whereinthe set of reference signal samples representing the training sequencebits and the set of rotation elements depending on the modulationapplied to the digital data prior to transmission are arranged as anextended training sequence matrix; and wherein the manipulating stepresults in an extended channel impulse vector which comprises anestimate of the DC offset (a_(dc)) and a plurality of the channelimpulse response elements (h), the manipulation carried out with theextended reference matrix and the received signal samples to generatethe extended channel impulse vector h_(e) being as follows: ĥ _(e)=(δ² C_(hh) ⁻¹ +X _(e) ^(H) X _(e))⁻¹ X _(e) ^(H) y, where$C_{hh}^{- 1} = \begin{pmatrix}{{1/h_{0}^{*}}h_{0}} & 0 & \ldots & \ldots & 0 \\0 & {{1/h_{1}^{*}}h_{1}} & 0 & \ldots & 0 \\\ldots & \ldots & \ldots & \ldots & ... \\\ldots & \ldots & \ldots & {{1/h_{i}^{*}}h_{i}} & \ldots \\0 & 0 & \ldots & \ldots & {{1/d}\quad c^{*}d\quad c}\end{pmatrix}$

and where h_(e) represents the extended channel impulse vector, X_(e)represents the extended reference matrix, y represents the receivedsignal samples and X_(e) ^(H) represents the complex conjugate transposeof the extended reference matrix.
 12. The method of claim 10 wherein thea priori information is generated in a preliminary estimation step. 13.The method of claim 10 wherein the a priori information is pre-stored.14. The method of claim 10, wherein the squared distance function is anLMMSE function.
 15. The method of claim 14 wherein the squared distancefunction is F=|y−X.h−e.a_(dc)|².
 16. A system for simultaneouslydetermining a DC offset and a channel impulse response in a signalreceived from a first station by a second station via a communicationchannel in a mobile communication system, the signal comprising digitaldata and a set of training sequence bits modulated prior totransmission, the method comprising: circuitry for receiving andsampling the signal to produce a plurality of received signal samplesfrom the training sequence portion of the signal, the received signalsamples possibly including a DC offset; a memory holding a set ofreference signal samples representing the training sequence bits and aset of rotation elements depending on the modulation applied to thedigital data prior to transmission; an extended channel impulse responsecalculation unit for manipulating the received signal samples with thereference signal samples and the set of rotation elements in such a wayas to simultaneously estimate the DC offset (a_(dc)) and the channelimpulse response (h) by minimising a squared distance function; andmeans for extracting the DC offset from the simultaneous estimateperformed by the extended channel impulse response calculation unit. 17.A system according to claim 16 wherein the squared distance function isF=|y−X.h−e.a_(dc)|², where y represents the received signal samples, Xrepresents the training sequence samples and e represents the set ofrotation elements.
 18. A system according to claim 17, which comprisescircuitry for removing the DC offset from received signal samplesrepresenting the digital data portion of the signal.
 19. A systemaccording to claim 17, which comprises combining circuitry for combiningthe extracted DC offset with the set of rotation elements prior toremoval of the DC offset from the received signal samples representingthe digital data portion of the signal.
 20. A system according to claim16, which comprises an equalisation circuit operable to remove from thereceived signal the effects of the communication channel for the signalusing the channel impulse elements extracted from the simultaneousestimate performed by the extended channel impulse response calculationunit.
 21. A system according to claim 16 further comprising means forproviding a priori information to the extended channel impulse responsecalculation unit.
 22. The system of claim 21 wherein said meanscomprises an impulse response estimation block.
 23. The system of claim21 wherein said means comprises a memory storing said a prioriinformation.
 24. The system of claim 21 in which the extended channelimpulse response calculation unit is a LMMSE.
 25. The system of claim 24wherein the extended channel impulse response is: ĥ _(e)=(δ² C _(hh) ⁻¹+X _(e) ^(H) X _(e))⁻¹ X _(e) ^(H) y, where$C_{hh}^{- 1} = \begin{pmatrix}{{1/h_{0}^{*}}h_{0}} & 0 & \ldots & \ldots & 0 \\0 & {{1/h_{1}^{*}}h_{1}} & 0 & \ldots & 0 \\\ldots & \ldots & \ldots & \ldots & ... \\\ldots & \ldots & \ldots & {{1/h_{i}^{*}}h_{i}} & \ldots \\0 & 0 & \ldots & \ldots & {{1/d}\quad c^{*}d\quad c}\end{pmatrix}$

and where h_(e) represents the extended channel impulse vector, X_(e)represents the extended reference matrix, y represents the receivedsignal samples and X_(e) ^(H) represents the complex conjugate transposeof the extended reference matrix.
 26. The system of claim 21 wherein thesquared distance function is F=|y−X.h−e.a_(dc)|², where y represents thereceived signal samples, X represents the training sequence samples ande represents the set of rotation elements.
 27. A method of determining aDC offset in a signal received from a first station by a second stationvia a communication channel in a mobile communication system, the signalcomprising digital data and a set of training sequence bits modulatedprior to transmission, the method comprising: generating an extendedreference matrix having m+1 columns where m columns contain referencesignal samples representing the training sequence bits and the m+1column contains a set of rotation elements depending on the modulationapplied to the digital data prior to transmission; receiving andsampling the signal to produce a plurality of received signal samplesfrom the training sequence portion of the signal, the received signalsamples possibly including a DC offset; and manipulating the receivedsignal samples with the extended reference matrix to produce an extendedchannel impulse vector comprising m channel impulse elementsrepresenting the communication channel and a further elementrepresenting the DC offset.
 28. A method of correcting for a DC offsetin a signal received from a first station by a second station via acommunication channel in a mobile communication system, the signalcomprising digital data and a set of training sequence bits modulatedprior to transmission, the method comprising: receiving and sampling thesignal to produce a plurality of received signal samples from thetraining sequence portion of the signal, the received signal samplespossibly including a DC offset; manipulating the received signal sampleswith an extended reference matrix having m+1 columns where m columnscontain reference signal samples representing the training sequence bitsand the m+1 column contains a set of rotation element depending on themodulation applied to the digital data prior to transmission to producean extended channel impulse vector comprising m channel impulse elementsrepresenting the communication channel and a further elementrepresenting the DC offset; extracting a DC offset from the extendedchannel impulse vector; and correcting the set of received signalsamples in the digital data portion of the signal by removing the thusdetermined DC offset.